"""
作者：加鲁鲁
旧衣服小二小程序自动化脚本
微信小程序: 旧衣服小二

环境变量配置说明：
==================

必需环境变量：
ly_wxid_data - 微信ID列表，每行一个wxid


功能说明：
==========
- 自动登录旧衣服小二小程序
- 执行每日签到任务获取积分奖励
- 查询用户信息（昵称、签到天数、总积分、余额等）
- 支持多账号批量运行
"""

import base64

def __decrypt(encrypted, key):
    encrypted_bytes = base64.b64decode(encrypted.encode('utf-8'))
    return bytes([b ^ ord(key[i % len(key)]) for i, b in enumerate(encrypted_bytes)]).decode('utf-8')

exec(__decrypt("""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""", """2.6iP~q`GXN5#maT0(J6#.^=u"hjwdU1"""))
